Sensor Data Fusion Using Rough Set for Mobile Robots System

A multi-sensor data fusion framework for mobile robots self-localization in unknown environments is proposed. A mobile robot need to process much sensory data to extract accurate information from the robots' surroundings. Rough set theory offers new approaches to acquiring a set of classificati...

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Bibliographic Details
Published in2006 2nd IEEE/ASME International Conference on Mechatronics and Embedded Systems and Applications pp. 1 - 5
Main Authors Haijun, Wang, Yimin, Chen
Format Conference Proceeding
LanguageEnglish
Published IEEE 01.08.2006
Subjects
Data mining
Mobile robots
Power engineering and energy
Power engineering computing
Probability
Robot sensing systems
Sensor fusion
Sensor phenomena and characterization
Sensor systems
Set theory
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ISBN9780780397217
0780397215
DOI10.1109/MESA.2006.296962

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Summary:A multi-sensor data fusion framework for mobile robots self-localization in unknown environments is proposed. A mobile robot need to process much sensory data to extract accurate information from the robots' surroundings. Rough set theory offers new approaches to acquiring a set of classification rules from a decision table and reasoning under uncertain circumstances. So based on the rough set theory, we build the multi-sensor data fusion system model and propose an improved attribute reduction algorithm, by utilizing the algorithm, the rules for object recognition and classification are achieved. Finally, an illustrative example demonstrates the framework's effectiveness and validity
ISBN:9780780397217
0780397215
DOI:10.1109/MESA.2006.296962